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Performance Evaluation for GEM Listed Companies Based on Support Vector Machine

Junfei Chen, Fan Jiang, Zeyuan Huang, Xian Fu

Abstract



The performance evaluation of listed companies is an important content for the enterprise?s operation and management. In this paper, the performance evaluation of Growth Enterprise Market (GEM) listed companies in China is studied based on the support vector machine (SVM) which can solve the small sample, non-linear, multiple attribute decision-making problems. The performance evaluation index system for the Chinese GEM listed companies, including six aspects, i.e., profitability, operating efficiency, solvency, development potential, discipline and law abiding and contribution, is established based on the theories and methods of performance evaluation of listed companies. The SVM-based performance evaluation model is proposed for the performance evaluation of Chinese GEM listed companies. Ten typical Chinese GEM listed companies are chosen and their performances are computed. The results show the model is effective for evaluating the performance of listed companies and can provide decision-making for the management of China's GEM.

Keywords


Support Vector Machine , Listed Companies, Growth Enterprise Market, Performance Evaluation.

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